Senior Applied ML Engineer, Graph Neural Network, ML Frontiers

Requirements

• Bachelor's degree or equivalent practical experience.
• 5 years of experience with software development in one or more programming languages.
• 2 years of experience with C++ and Python.
• Experience with machine learning (ML)/AI in a software development environment.

Nice to haves

• 5 years of experience with data structures and algorithms.
• 2 years of experience with applied machine learning/machine learning research.
• Experience with one or more neural network frameworks: PyTorch, TensorFlow or Jax.
• Experience with decision trees.

What You'll Be Doing

• Develop feature development (design, coding, doc writing, and maintenance), research exploration (reading papers, benchmarking, and possibly going/submitting to ML conferences), collaborate with clients (from small consultation to large engagements) and partners (e.g., Google Research).
• Implement a distributed graph sampling algorithm (without Flume), benchmark a newly published graph convolution layer in JAX, or develop an interactive Colab component to analyze a trained model.
• Participate in brainstorming and help define future applied research, engineering, and product roadmap priorities.
• Focus on Graph Neural Networks within Graph Flow, collaborate with the remainder of the ML Frontiers teamwhile working on LLM agents and decision forests.

Perks and Benefits

• Google Cloud’s mission to make businesses successful through AI.
• Opportunity to bridge the gap between pioneering models and a massive product vehicle reaching billions.
• Talent density and AI-powered tools for rapid development.
• Culture of empowerment and a bias to action.